Associating a task with a user based on user selection of a query suggestion

ABSTRACT

Methods and apparatus related to associating a task with a user based on the user selecting a task suggestion that is provided to the user in response to a user query. In some implementations, the task may be identified based on similarities between the words and/or phrases of the user query and a task suggestion that is associated with a task. In some implementations, the task may be identified based on user data associated with the user. In some implementations, the task may be associated with additional information related to completing the task.

BACKGROUND

This specification is directed generally to providing a user with a tasksuggestion in response to a query and associating a task with the userwhen the user selects the task suggestion.

A user may sometimes utilize a search engine to locate informationregarding a task that requires completion. For example, a user maysearch for information regarding booking a flight in anticipation ofneeding to do so in the future. A user may additionally and/oralternatively utilize other applications to locate information and/or tostore information related to the task.

SUMMARY

The present disclosure is directed to methods and apparatus foridentifying a query from a user and providing a suggestion for the querythat is a task suggestion related to a task. The user may be associatedwith the task when the user selects the task suggestion. In someimplementations, tasks may be identified based on one or more terms ofthe query. In some implementations, tasks may be identified based ondata that is associated with the user. In some implementations,additional information related to completing a task may be associatedwith the task.

In some implementations, a method is provided and include the steps of:identifying a query of a user; identifying a plurality of suggestionsfor the query, the suggestions including at least one task suggestionassociated with at least one task; providing one or more of thesuggestions to the user, the provided suggestions including the tasksuggestion associated with the at least one task; receiving a userselection of the task suggestion; and associating the at least one taskwith the user in response to receiving the user selection of the tasksuggestion.

This method and other implementations of technology disclosed herein mayeach optionally include one or more of the following features.

The method may further include the step of providing an indication ofthe at least one task in combination with providing the task suggestionto the user. The user selection of the task suggestion may be a userselection of the indication of the at least one task.

The method may further include the step of identifying a task type,wherein the indication of the at least one task is based on the tasktype. The indication of the at least one task may be a graphicalindication of the task type.

The method may further include the step of determining the at least onetask associated with the task suggestion. The task may be determinedbased on one or more terms of the task suggestion. The task may bedetermined based on user data associated with the user. The user datamay include at least one of user contacts, user webpage navigationhistory, and user e-mails.

The method may further include the step of generating the tasksuggestion based on user data associated with the user. The task may bebased on user data associated with the user.

The method may further include the steps of: determining additionalinformation related to completion of the task; and associating theadditional information with the task. The method may further include thestep of identifying a task type for the task, and determining theadditional information related to completion of the task may be based onthe identified task type. The additional information may be based onuser data associated with the user. The user data may include at leastone of user contacts, user webpage navigation history, and user e-mails.

Other implementations may include a non-transitory computer readablestorage medium storing instructions executable by a processor to performa method such as one or more of the methods described herein. Yetanother implementation may include a system including memory and one ormore processors operable to execute instructions, stored in the memory,to perform a method such as one or more of the methods described herein.

Particular implementations of the subject matter described hereinassociate one or more tasks with a user based on a selection of a querysuggestion by the user, wherein the query suggestion is associated withthe one or more tasks. These tasks represent actions that may be takenby the user. The tasks may be based on terms of the query suggestionand/or may additionally be identified based on information associatedwith the user. Particular implementations of the subject matterdescribed herein may further associate additional information related tocompleting a task with the task based on user input and/or one or moreadditional sources.

It should be appreciated that all combinations of the foregoing conceptsand additional concepts discussed in greater detail herein arecontemplated as being part of the inventive subject matter disclosedherein. For example, all combinations of claimed subject matterappearing at the end of this disclosure are contemplated as being partof the inventive subject matter disclosed herein.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of an example environment in whichimplementations of a method of associating tasks with a user based on auser selecting a task suggestion may be implemented.

FIG. 2 is a flow chart illustrating an example method of associating atask with a user based on the user selecting a task suggestion from aplurality of query suggestions.

FIG. 3 is a flow chart illustrating an example method of determiningadditional information related to completing a task associated with auser.

FIG. 4A illustrates a partial screenshot of an example graphical userinterface that can be used to provide query suggestions to a user.

FIG. 4B illustrates another partial screenshot of an example graphicaluser interface that can be used to provide query suggestions to a user.

FIG. 4C illustrates another partial screenshot of an example graphicaluser interface that can be used to provide query suggestions to a user.

FIG. 4D illustrates another partial screenshot of an example graphicaluser interface that can be used to provide query suggestions to a user.

FIG. 4E illustrates a partial screenshot of an example graphical userinterface that can be used to prompt a user to provide additionalinformation about a task.

FIG. 4F illustrates a partial screenshot of an example graphical userinterface that can be used to provide query suggestions and additionaltask completion information to a user.

FIG. 4G illustrates a partial screenshot of an example graphical userinterface that can be used to provide query suggestions with task typeindications to a user.

FIG. 5 illustrates a block diagram of an example computer system.

DETAILED DESCRIPTION

In some implementations, a user may utilize one or more applications tosubmit a query to record and/or locate information regarding one or moretasks that the user may have interest in completing. For example, a usermay use a search engine to submit the query “pay my cell phone bill” tolocate information regarding the process of paying a cellular telephonebill and/or to store information related to the process, such as storing“pay my cell phone bill” as a reminder in a calendar application. Also,for example, a user may submit the search query “flight information” tolocate information about future flights. The user may be provided one ormore query suggestions that share one or more aspects with the submittedquery of the user. The provided query suggestions may include one ormore task suggestions. A task suggestion is a query suggestion that isassociated with a task. For example, a query suggestion may beassociated with the task of paying a cellular telephone bill, and/or thetask of booking airline flights, based on the user submitting theexample queries.

In some implementations, a query suggestion may be an auto completesuggestion for a partial query of the user. For example, the user mayenter the partial query “pa” and query suggestions that are autocomplete suggestions for the partial query may be provided to the user,such as “pay my cell phone bill.” The provided query suggestion mayinclude one or more task suggestions. A task suggestion may be based onthe partial query of the user and may be associated with a task. Forexample, the partial query “pa” may result in a provided task suggestion“pay my cell phone bill” associated with a task for the user to pay acellular phone bill.

In some implementations, a task may be a representation of a futureevent and/or an intended action. For example, a task may be anappointment that will occur in the future. Also, for example, a task maybe associated with a transaction to be completed. Examples of tasks mayinclude, for example, paying a bill, making a reservation, arriving atand/or departing from a location, and/or purchasing an item.

In some implementations, a task may be categorized with a task type. Atask type may be descriptive of the requirements to perform a taskand/or the purpose for the task. For example, a task may be related topaying a cellular phone bill. The task may be categorized as a remindertask because the task may be to remind a user to pay a bill, and/or thetask may be categorized as a purchase task because the task may be topurchase a product and/or service. Other examples of task types mayinclude event tasks, appointment tasks, and/or search query tasks.

In some implementations, a task may be associated with additionalinformation pertaining to the completion of the task. For example, atask may be to reserve an airline flight for an upcoming trip.Additionally, the task may be associated with flight times,destinations, airline information, and/or the purpose of the trip. Insome implementations, additional information about a task may beassociated with a task based on input of a user. For example, in someimplementations, the additional information about a task may beidentified from one or more additional sources, such as user-createdand/or user-edited documents. In some implementations, the query thatwas provided by the user may include additional information about atask. For example, a flight booking task that is associated with a tasksuggestion that is provided to the user based on the user entering thequery “flights LAX” may be further associated with additionalinformation based on the presence of the airport designation “LAX” inthe query, such as the location of the airport and specific flightinformation about the airport. In some implementations, additionalinformation about a task may be identified from one or more additionaldatabases, such as an entity database.

In some implementations, entities are topics of discourse. In someimplementations, entities are persons, places, concepts, and/or thingsthat can be referred to by a text fragment (e.g., a term or phrase) andare distinguishable from one another (e.g., based on context). Forexample, the text “bush” in a query or on a webpage may potentiallyrefer to multiple entities such as President George Herbert Walker Bush,President George Walker Bush, a shrub, and the rock band Bush. In someimplementations, an entity may be referenced by a unique entityidentifier that may be used to identify the entity. The unique entityidentifier may be associated with one or more properties associated withthe entity and/or with other entities. For example, in someimplementations one or more entity database may include propertiesassociated with unique identifiers of one or more entities. For example,for each of a plurality of entities, a mapping (e.g., data defining anassociation) between the entities and one or more properties and/orother entities related with the entity may be identified in the entitydatabase. For example, a unique identifier for the entity associatedwith “LAX” may be associated with a name or alias property of “LAX,”another alias property of “Los Angeles International Airport” (analternative name by which LAX is often referenced), a phone numberproperty, an address property, and/or an entity type property of“airport” in the entity properties database. Additional and/oralternative properties may be associated with an entity in one or moredatabases such as an entity database. In this specification, the term“database” will be used broadly to refer to any collection of data. Thedata of the database does not need to be structured in any particularway, or structured at all, and it can be stored on storage devices inone or more locations. Thus, for example, the database may includemultiple collections of data, each of which may be organized andaccessed differently.

Referring to FIG. 1, a block diagram is illustrated of an exampleenvironment in which implementations of a method of associating taskswith a user based on a user selecting task suggestions may beimplemented. The environment includes a computing device 105 with a webbrowser 110, a search engine 125, a query suggestion engine 120, a taskrecognition engine 115, and a content database 130. The environment alsoincludes a communication network 101 that enables communication betweenvarious components of the environment.

The computing device 105 executes one or more applications, such as webbrowsers (e.g., web browser 110), that enable the user to formulatequeries and submit completed queries to the search engine 125. In someimplementations, queries may be submitted directly to the search engine125 from the computing device 105. In some implementations, completedqueries may be submitted from the query suggestion engine 120 to thesearch engine 125. In some implementations, queries may be additionallyand/or alternatively submitted to other engines, such as those discussedherein. For example, a query may be submitted to task recognition engine115 to associate a task with a user based on one or more terms in thequery.

In some implementations, a query is one or more terms that a user maysubmit to an engine to request one or more results. In someimplementations, the engine may be a search engine that shares one ormore aspects with search engine 125. In some implementations, the searchengine 125 may be an internet search engine and may provide one or moreweb-based documents in response to a query. In some implementations, aquery may be submitted to a non-search engine application and the usermay be provided with one or more options and/or documents that arespecific to that application in response to the submission of a query.For example, the user may submit “go to gym” to a query entry interfaceof a calendar application and the user may be provided with an option tocreate a reminder task to go to the gym and/or the user may be providedwith an existing reminder and/or appointment task to go to the gym thathas been previously submitted to the calendar application.

In some implementations, a partial query may be submitted to a querycompletion engine and one or more query suggestions may be provided tothe user in response to the partial query. In some implementations, auser may indicate a completed query by entering a carriage return and/orother character. In some implementations, a user may indicate acompleted query by selecting a search button or other submission buttonin a user interface presented to the user. In some implementations, auser may indicate a completed query by speaking a command in a speechuser interface. In some implementations, a user may indicate a completedquery by pausing more than a predetermined amount of time duringentering of the query. In some implementations, an application mayprovide query suggestion engine 120 with partial queries for eachcharacter of a query as it is typed or otherwise entered by the user. Insome implementations, an application may provide multiple characters ata time, optionally following a pause by the user between characterentries.

In some implementations, multiple query suggestions may be included in asingle search query (e.g., prior to a user indication that the searchquery is complete). For example, a user interface of the computingdevice 105 may allow a user to select multiple query suggestions insuccession, allowing the user to build a search query one word or onephrase at a time. A phrase can include one or more words. When the userselects multiple query suggestions, the query can include each of theselected query selections in the sequence that they were selected. Aftereach selection of a query suggestion, the computing device 105configures the user interface to receive additional query content ratherthan indicating a completed query in response to user selection of aquery suggestion.

As an example, when a user selects a query suggestion, the selectedquery suggestion is added to the partial query, forming an extendedquery. The computing device 105 then presents new query suggestions forthe extended query. By selecting one of the new query suggestions, theuser can add it to the extended query, and can continue to addadditional query suggestions (or other input) until the user indicatesthat the query is complete.

In some implementations, one or more query suggestions may be providedto the user in response to the user entering a partial query. The querysuggestion may be, for example, one or more terms that are responsive tothe terms that were entered by the user and one or more additional termsthat may be likely completions to the partial query that has beenentered by the user. For example, the user may enter “pay my c” and beprovided with one or more query completion suggestions, such as “pay mycell phone bill” and “pay my credit card.” In some implementations, thequery suggestion may be associated with a task and the user may selectthe query suggestion to associate the task with the user. In someimplementations, the query suggestion may be selected by the user andsubmitted to a search engine to identify one or more webpages that mayinclude content that is related to the query. In some implementations,the query suggestion that is selected by the user may be submitted to anapplication and the user may be provided with content from theapplication and/or further action that may be taken by the user based onthe selected query suggestion. For example, a user may submit thepartial query “remind me to go to” into a query submission interface ofa calendar application and be provided with a list of query suggestionsthat includes “remind me to go to the gym” and “remind me to go to thedoctor.” By selecting one of the query suggestions, a task may beassociated with the user and/or a reminder may be added to a calendar inthe calendar application.

In some implementations, a user may interact with the search engine 125through a web browser 110 on a client computing device 105. Thecomputing device 105 may be, for example, a desktop computer, a laptopcomputer, a cellular phone, a smartphone, a personal digital assistant(PDA), a tablet computer, a wearable computing device (e.g., a digitalwatch, earpiece, glasses), a navigation system, and/or another computingdevice. The computing device 105 and the search engine 125 each includememory for storage of data and software applications, a processor foraccessing data and executing applications, and components thatfacilitate communication over a communication network 101. Theoperations performed by the client computing device 105, the browser110, and/or the search engine 125 may be distributed across multiplecomputer systems.

The search engine 125 receives a query and executes the query against asearch engine content database (e.g., content database 130) of availabledocuments such as web pages, images, text documents, and/or multimedia.For the purposes of this specification, a document is any data that isassociated with a document address. Documents include webpages, wordprocessing documents, portable document format (PDF) documents, images,video, audio, e-mails, calendar entries, task entries, and feed sources,to name just a few. The documents may include content such as, forexample, words, phrases, pictures, audio, task identifiers, entityidentifiers, etc.; embedded information (such as meta information and/orhyperlinks); and/or embedded instructions (such as JavaScript scripts).The search engine 125 identifies content that matches the submittedquery and responds by generating search results that are transmitted toone or more devices in a form that is useful for the devices. Forexample, in response to a query from the computing device 105, thesearch engine 125 may transmit a plurality of search results to bedisplayed in the web browser 110 that is executing on the computingdevice 105. The content database 130 may include one or more storagemediums. For example, in some implementations the content database 130may include multiple computer servers each containing one or morestorage mediums.

Applications executing on the computing device 105 may also providepartial queries being formulated by users, before the users haveindicated completion of the queries. The applications may be, forexample, a web browser 110, a toolbar running in the web browser 110, ane-mail application, a text-messaging application, a calendarapplication, a reminder application, a task application, and/or a searchclient running on the computing device 105. In some implementations, theapplications provide each character of a query as it is typed orotherwise entered by the user. In some implementations, the applicationsprovide multiple characters at a time, optionally following a pause bythe user between character entries.

A partial query is a query formulated by a user prior to an indicationby the user that the query is a completed query. In someimplementations, a user may indicate a completed query by entering acarriage return and/or other character. In some implementations, a usermay indicate a completed query by selecting a search button or othersubmission button in a user interface presented to the user. In someimplementations, a user may indicate a completed query by speaking acommand in a speech user interface. In some implementations, a user mayindicate a completed query by pausing more than a predetermined amountof time during entry of the query. Other forms of providing a partialquery and/or indicating a completed query may additionally and/oralternatively be utilized.

In response to a partial query entered by a user, the computing device105 may facilitate entry of user input by providing suggested inputs tothe user. For example, when the user enters one or more characters, thecomputing device 105 can provide query suggestions that are selectedusing the one or more characters. In some implementations, the querysuggestions may be provided to the computing device 105 by querysuggestion engine 120. The query suggestions that are provided mayinclude words or phrases that include the one or more characters thatwere entered by the user. For example, complete words or extendedphrases can be suggested for partial words or partial phrases that auser has entered (e.g., spoken, or typed using a physical or virtualkeyboard). The query suggestions can also include words or phrases thatare similar to (e.g., synonyms or spelling corrections of) the userinput. The user can select one of the provided query suggestions toenter the text of the selected query suggestion. As referred to herein,a “selection” may include, for example a mouse-click, a click-through, avoice-based selection, a selection by a user's finger on apresence-sensitive input mechanism (e.g., a touch-screen device), and/orany other appropriate selection mechanism.

The query suggestions may be displayed to a user in a user interface ofthe computing device 105. For example, the query suggestions may bedisplayed within a cascaded drop down menu of the search field of anapplication, such as a web browser 110 executing on the computing device105, as the user is typing the query, such as the partial userinterfaces that are illustrated in FIGS. 4A through 4D and describedherein. Also, for example, the query suggestions may be displayed in aplurality of separately selectable cells arranged in one or more rows orcolumns in a user interface. For example, query suggestions that areassociated with a task may be displayed in a separate column from otherquery suggestions. In some implementations, one or more search resultsfor a query suggestion may optionally be displayed as the user is typingthe query. In some implementations, query suggestions that are relatedto a task may be displayed with an indication, such as an icon and/orwords, to indicate to the user that the query suggestion is a tasksuggestion and may be utilized to associate a task with the user. Forexample, the suggestion “pay my cell phone bill” in the cascaded menuillustrated in FIG. 4B is annotated with “Create Task” to designate thatthe suggestion is a task suggestion.

In some implementations, in response to a partial query being entered atcomputing device 105, the search engine 125 may receive the partialquery and forward the partial query to the query suggestion engine 120.In some implementations, in response to a partial query being entered atcomputing device 105, the one or more applications executing on thecomputing device 105 may optionally directly forward the partial queryto the query suggestion engine 120. For example, in someimplementations, the browser 110 may directly forward the partial queryto the query suggestion engine 120. The query suggestion engine 120 mayinclude memory for storage of data and software applications, aprocessor for accessing data and executing applications, and componentsthat facilitate communication over the communication network 101. Thequery suggestion engine 120 may match a submitted partial query to oneor more of a plurality of query suggestions that are an appropriatematch to the query. In some implementations, the query suggestions mayrepresent potential completed queries that may be provided to a user toenable the user to choose one of the query suggestions as a basis forutilization in a search application or other information retrieval orstorage application. In some implementations, one or more of the querysuggestions may be task suggestions and associated with a task that isrelated to the submitted query.

In some implementations, the query suggestions may include thosedetermined based on a list of past user queries, a list of automaticallygenerated queries, and/or real time automatically generated queries. Insome implementations, the query suggestions may include those identifiedbased on data retrieved from a database. For example, the querysuggestion engine 120 may use prefix based matching to identify querysuggestions from a list of past user queries and/or from matches toentries in the content database 130. Any listing of past user queries,past automatically generated queries, and/or queries that are related toone or more tasks, may optionally be stored in a query suggestioncontent database such as content database 130, for potential utilizationas query suggestions and/or as a basis for query suggestions. The querysuggestions provided by the query suggestion engine 120 may representwords or phrases that a user may want to include in addition to orinstead of the query actually being typed. In some implementations, oneor more of the provided query suggestions may be a task suggestion. Forexample, a query suggestion may be provided that shares one or moreaspects with a task, such as the query suggestion “book a flight” andthe task of booking a flight. A task may be associated with a querysuggestion based on one or methods described herein.

In some implementations, the content database 130 may include one ormore query suggestions that have been determined and/or scored, and/orotherwise ranked. In some implementations, the query suggestion engine120 and/or task recognition engine 115 may provide the query suggestionsto a user via the search engine 125, the query suggestion engine 120,and/or to the computing device 105 directly. In some implementations thequery suggestion engine 120 may determine scores for one or more querysuggestions; determine which query suggestions to provide to a user;and/or rank one or more query suggestions. For example, the querysuggestion engine 120 may sort one or more query suggestions based atleast in part on scores assigned to each of such query suggestions. Theranking may be based on one or more factors, such as the number of termsin the query suggestions, the length of term(s) in the querysuggestions, and/or display parameters of the computing device 105. Insome implementations, ranking of the query suggestions may be utilizedto determine which query suggestions are provided to a user and/or inwhich order the query suggestions are displayed to the user.

In some implementations, the task recognition engine 115 may determinewhether a task should be associated with a query suggestion based on oneor more indications of the likelihood that the user has interest inbeing associated with the task. For example, in some implementations,the user may enter “pay c” without having interest in initiating a cellphone payment reminder task. In other instances, the user may enter “payc” and have interest in a cell phone payment reminder task beinginitiated. In some implementations, the task recognition engine 115 mayidentify one or more additional documents that are related to a cellularphone of a user, such as an email that includes a cellular phone bill,and determine that the user has a cellular phone and that the user islikely to have interest in a reminder task based on the document. Thetask may be more likely to be associated with a query suggestion of “paymy cell phone” for the partial query “pay my c” than if the taskrecognition engine 115 had not identified further information indicatingthat the user has a cellular phone.

In some implementations, the task recognition engine 115 may determinewhether to associate a task with a query suggestion based on theapplication that the user is utilizing to submit the query and one ormore contextual terms in a query. For example, the user may submit thequery “cell phone payment” to a search engine via web browser 110 andthe task recognition engine 115 may determine that the user is morelikely to be initiating a web search than the user has interest in tasksuggestions. Also, for example, the user may submit the query “make acell phone payment” to a search engine of web browser 110 and the taskrecognition engine 115 may determine that the user is more likely tohave interest in a task suggestion than the submission of the query“cell phone payment” based on the query including one or more terms,such as “make a” that indicate a likely task. Also, for example, one ormore key words in a query may indicate that the query is being submittedto specifically return task suggestions, such as submitting “Task: cellphone payment” as a query in browser 110.

As another example, the user may be more likely to have interest in areminder task when the user submits a query in a calendar application.The user may submit the same query “cell phone payment” in a calendarapplication and more likely be provided with a task suggestion of“reminder to pay cell phone” based on the greater likelihood that a userwould have interest in a reminder task when user submits the query inthe calendar application.

In some implementations, one or more task suggestions may be boosted ina ranked list of query suggestions to increase the likelihood that theuser will be provided a given task suggestion. For example, a scoringassociated with a task suggestion may be increased to a score that ishigher than the score the query suggestion would otherwise have in alist of ranked query suggestions. Also, for example, a task suggestionmay be boosted one or more places in a ranked list of query suggestions.In some implementations, a task suggestion may be included in a list ofprovided query suggestions that would otherwise have not been includedin the list if a task was not associated with the query suggestion. Forexample, the task suggestion “pay my cell phone bill” may be included ina list of query suggestions for the query “cell phone,” while the querysuggestion “pay my cell phone bill” that is not associated with a taskwould not appear in the same list of provided query suggestions. In someimplementations, a task suggestion may be associated with a task basedon user data and/or information that is associated with the user; and/orentities in a content database that are related to one or more terms ofa task. For example, a user may be provided directions to “Business1” asa task suggestion for the task “pay cell phone bill to Business1” basedon the association of “Business1” with an address in a database and/oran address for “Business1” that is identified in an email of the user.

In some implementations, a query suggestion that has been identified bythe query suggestion engine 120 may be associated with a task based onthe presence of one or more terms in the query suggestion. The terms mayinclude one or more phrases that are commonly associated with a task andthat commonly appear in query suggestions that are related to a task.For example, the query suggestion “pay my cell phone bill” may beidentified as a task suggestion based on a query that was entered by theuser. Task recognition engine 115 may identify the phrase “pay my” inthe query suggestion as potentially related to the user intending to paya bill and associate the task of paying a bill with the task suggestion.If the user selects the task suggestion, task recognition engine 115 mayoptionally further prompt the user for additional information regardingthe task, such as the recipient of the payment, the address to sendpayment, and/or the date when the bill is due.

In some implementations, the task recognition engine 115 may identify atask that shares an aspect with a query suggestion based on similaritybetween one or more terms of the query suggestion and a property of thetask. The task recognition engine 115 may compare one or more terms of aquery with a list of tasks and associated properties that are likely tobe present in a query suggestion that is related to the correspondingtask. For example, the query suggestion “cellular phone bill” may beidentified as similar to a task of “Pay my cellular phone bill” and theuser may be provided with the task suggestion based on the similaritybetween one or more key words that are associated with the task and thequery suggestion (i.e., cellular, phone, and bill). In someimplementations, task recognition engine 115 may use prefix basedmatching to identify query suggestions from a list of task suggestions(e.g., “pay cell phone bill” as similar to the query “pay cell”) and/orthe task recognition engine 115 may use term similarity to identify oneor more terms in a query that are similar to one or more terms of a tasksuggestion (e.g., the task suggestion “cell phone payment by phone” assimilar to the given query “pay my cellular phone bill”).

In some implementations, task recognition engine 115 may identify one ormore tasks that are specific to a user and provide a task suggestionbased on similarity between user-specific information and the providedquery. In some implementations, the task recognition engine 115 mayidentify tasks that are specific to the user based on one or moredocuments that are associated with the user, such as emails, recentlydisplayed webpages, search history, calendar entries, social medianotifications, text notifications, and/or contacts lists. In someimplementations, task recognition engine 115 may identify and/orformulate a task suggestion based on one or more known latent attributesof the user. For example, the task recognition engine 115 may identifythe geographic location of the user, the age of the user, and/or theoccupation of the user from one or more sources, and the formulated tasksuggestion may be specific to the one or more latent attributes. In someimplementations, task recognition engine 115 may identify and/orformulate a task suggestion that shares one or more aspects with a givenidentified task and provide the task suggestion in response to a querythat shares similarities with the task suggestion. For example, the taskrecognition engine 115 may identify a potential task for a user from auser's calendar entry of “Bob's Birthday party” on April 4. The user mayenter the query “Buy present” and the task recognition engine 115 mayprovide the task suggestion “Buy Bob a birthday present” based on theidentification of the calendar entry and the similarity of the text ofthe calendar entry and the query. A task may be associated with the userand/or suggested to the user based on the user selecting the tasksuggestion “Buy Bob a birthday present,” and the user may be associatedwith the reminder task of “Buy Bob a birthday present by April 4” if theuser selects the provided task suggestion.

In some implementations, task recognition engine 115 may additionally oralternatively associate a task with the user when the user selects atask suggestion from the query suggestions that the query suggestionengine 120 provides to the user in response to a query. In someimplementations, the user may identify a task suggestion by selectingthe suggestion from a drop down list of query suggestions, such as thepartial graphical user interfaces in FIGS. 4A through 4D. For example,with reference to FIG. 4B, the user may select the task suggestion “paymy cell phone bill” by moving the cursor 440B over the task suggestion430B and left clicking on a mouse. In some implementations, tasksuggestions may be distinguished from query suggestions, such as thetask suggestion “pay my cell phone bill” in FIG. 4B, which is displayedwith the additional words, “Create Task.” In some implementations, atask may be associated with a user based on the user selecting aprovided task suggestion. In some implementations, the user may have theoption of utilizing a provided task suggestion as a search query withoutassociating a task with the user in addition to utilizing the querysuggestion as a task suggestion. For example, “Create Task” may beselectable and associate the task that is associated with thecorresponding task suggestion with the user. Alternatively, selectingthe query suggestion (e.g., selecting the text of the task suggestionwithout selecting “Create Task”) may utilize the task suggestion as anautocomplete suggestion and result in search results based on the querysuggestion without associating a task with the user.

In some implementations, the task recognition engine 115 may associateadditional information with a task based on additional information thatis provided to the task recognition engine 115 by the user and/or thatis available about the task. For example, the user may be prompted atthe time that the user selects the task suggestion to provide additionalinformation about the task utilizing a task information prompt that mayshare one or more characteristics with the task information promptillustrated in FIG. 4E and described herein. In some implementations,the task recognition engine 115 may identify additional informationabout a task based on one or more terms that are present in the querythat was provided by the user and/or present in an identified tasksuggestion. For example, the query suggestion “flights LAX” may beselected by the user and the airport designation “LAX” may be associatedwith the created task as additional information based on its presence inthe provided query suggestion. In some implementations, additionalinformation about a task may be available from one or more databases,such as an entity database. For example, for a task suggestion of“flights LAX,” a database may be utilized to identify mappings between“LAX” and a phone number and/or address of the LAX airport, which mayfurther be associated as additional information of a task of “Book aflight.”

In some implementations, task recognition engine 115 may identify a taskand/or additional information related to the completion of a task basedon mappings between multiple entities and/or mappings between entitiesand one or more entity properties. The task recognition engine 115 mayidentify the entities and/or entity properties by accessing one or moredatabases such as an entity database. For example, an entity databasemay include one or more knowledge graphs mapping entities and entityproperties and/or entities and other entities. In some implementations,task recognition engine 115 may determine a likely task and/or propertyof a task based on mappings between multiple entities and/or entitiesand entity properties, in combination with artificial intelligencehaving predictive capabilities. For example, in some implementations oneor more mappings between two or more entities may define relationshipsbetween the entities that may be utilized to determine task suggestions.For example, a calendar entry may include the terms “Buy present forBob's birthday.” Based on the terms, an entity associated with “birthdayparty” and an entity associated with the action of “buying a present”may be identified. Based on mapping in the entity database between theentities (e.g., the action of “buying a birthday present” as being atask that may be performed for a “birthday party”), a task suggestionmay be provided for the query that is associated with the task of“buying a birthday present.” Further information may be associated withthe task based on additional entities and/or actions mapped to “birthdayparty,” such as “directions to party” and/or “phone number for contact,”and additional information associated with the entities may beidentified from documents and/or other data of the user. For example, anentity associated with “birthday party” may be associated with an entityassociated with the action of “getting directions,” which may further beassociated with an entity associated with “address.” Contact informationfor “Bob” may be identified in a contacts application for a contact of“Bob,” which may include an address that may be potentially associatedwith the task. For example, the task of “go to Bob's party” may beassociated with address that was identified from the contact “Bob” inthe contacts application of the user. In some implementations, thelikelihood that the identified task suggestion is the correct tasksuggestion may be determined and optionally utilized in determining aconfidence level associated with the task suggestion and/or theconfidence level that additional information should be associated with atask.

Also, for example, a query may include the text “pay my cell phone bill”and/or a spoken query by a user may be identified as “pay my cell phonebill at Business 1.” The terms “pay cell” may indicate a predictedservice action and the text “Business 1” may indicate the service actionis related to an entity associated with “Business 1.” A service actionmay be associated with certain properties associated with an entity suchas, for example, one or more phone numbers that may be called to pay acellular phone bill, one or more e-mail addresses that enable payment,and/or one or more webpages that enable payment. A mapping between anentity associated with “Business 1” and properties of that entity thatmay indicate one or more phone numbers related to that entity that maybe contacted to submit payment, one or more e-mail addresses related tothat entity that enable payment, and/or one or more webpages related tothat entity that enable payment may be identified. One or more of themapped properties may be identified as additional information about atask. For example, a webpage that enables payment of a cellular phonebill and is mapped to the entity associated with “Business 1” may beidentified as additional task completion information. In someimplementations, a likelihood that identified additional information iscorrect additional information may be determined and optionally utilizedin determining a confidence level associated with the task. Additionaland/or alternative methods of identifying additional information relatedto the completion of a task in combination with artificial intelligencehaving predictive capabilities may be utilized.

In some implementations, task recognition engine 115 may identify tasksand/or additional information about tasks based on identification of oneor more properties of an entity and one or more terms and/or phrasesthat are present in a provided query and/or document. Associations oftasks and additional information may be identified from an entitydatabase that may share one or more aspects with content database 130.For example, task recognition engine 115 may identify an alias and/oradditional information associated with an entity from a provided query,a user calendar entry, or a user-created and/or user-edited document.The task recognition engine 115 may identify the entity that isassociated with the alias and/or additional information by accessing oneor more database such as an entity database. One or more additionalproperties associated with the entity, additional entities associatedwith the entity, and/or one or more additional properties associatedwith associated entities may be utilized as a task and/or as additionaltask information. For example, selected task suggestion of a user mayinclude the phrase “Fly to Los Angeles.” Task recognition engine 115 mayidentify the task suggestion as related to a task that is associatedwith the user and identify an “airport” entity that is associated with“fly” and “Los Angeles” in an entity database. The task recognitionengine 115 may identify an alias of the entity associated with “fly” and“Los Angeles” as “LAX” and associate the alias of the airport, LAX, withthe task that is related to the calendar entry. Additional informationabout flights and/or airport information may be associated with the taskbased on associated information in an entity database and/or otherdatabase. In some implementations, additional information may beidentified based on latent attributes of a user. For example, theorigination airport to associate with the task of “fly to Los Angeles”may be identified based on identifying the current location of the user(e.g., associating the origination location as “O′Hare” based onidentifying that the user is located in Chicago utilizing GPS data).

The communication network 101 facilitates communication between thevarious components in the environment. In some implementations thecommunication network 101 may include the Internet, one or moreintranets, and/or one or more bus subsystems. The communication network101 may optionally utilize one or more standard communicationstechnologies, protocols, and/or inter-process communication techniques.

In situations in which the systems discussed herein collect personalinformation about users, or may make use of personal information, theusers may be provided with an opportunity to control whether programs orfeatures collect user information (e.g., information about a user'ssocial network, social actions or activities, profession, a user'spreferences, or a user's current geographic location), or to controlwhether and/or how to receive content from the content server that maybe more relevant to the user. Also, certain data may be treated in oneor more ways before it is stored or used, so that personal identifiableinformation is removed. For example, a user's identity may be treated sothat no personal identifiable information can be determined for theuser, or a user's geographic location may be generalized wheregeographic location information is obtained (such as to a city, ZIPcode, or state level), so that a particular geographic location of auser cannot be determined. Thus, the user may have control over howinformation is collected about the user and/or used.

Many other configurations are possible having more or fewer componentsthan the environment shown in FIG. 1. For example, although the querysuggestion engine 120 and the task recognition engine 115 are eachillustrated alone in FIG. 1, it is understood that the query suggestionengine 120 and/or the task recognition engine 115 may optionally becombined with one another and/or with one or more of the search engine125 and/or the computing device 105 in some implementations.

Referring to FIG. 2, a flow chart illustrating an example method ofassociating a task with a user based on the user selecting a tasksuggestion from a plurality of query suggestions is provided. Otherimplementations may perform the steps in a different order, omit certainsteps, and/or perform different and/or additional steps than thoseillustrated in FIG. 2. The steps of the method illustrated in FIG. 2 maybe performed by one or more components illustrated in FIG. 1.

At step 200, a query from a user is identified. In some implementationsthe query may be entered by a user via a computing device executing aweb browser, such as computing device 105 and web browser 110. In someimplementations, the user may enter a complete query into the webbrowser 110 and indicate that the query is complete, such as byselecting a search button, stopping typing for a predetermined period oftime, speaking a voice command, and/or pausing while speaking. In someimplementations, the user may enter a partial query in anticipation ofreceiving suggested queries.

At step 205, one or more query suggestions are identified based on thequery that was identified in step 200. In some implementations, querysuggestion engine 120 may identify query suggestions for the providedquery as described herein. For example, for a partial query of “pa,” thequery suggestions illustrated in FIG. 4A may be obtained. The querysuggestions of FIG. 4A are illustrated in the drop-down box 420A. Forthe query “pa,” the query suggestions all contain “pa” as the prefix andcontain additional text to form a complete word or phrase starting with“pa.”

In some implementations, one or more of the identified query suggestionsmay be task suggestions. The task suggestions may share one or moreaspects with a task that may be performed by the user. For example,query suggestion engine 120 may identify the query suggestion “pay mycell phone bill” and task recognition engine 115 may associate the taskof paying a cellular phone bill with the query suggestion based on thelikelihood that the user has interest in paying a cellular phone bill.In some implementations, the task may be associated with the querysuggestion based on similarity between the query suggestion and thetask. In some implementations, the task recognition engine 115 mayassociate a task with the query suggestion based on user attributesand/or information from one or more user-created and/or user-editeddocuments. For example, task recognition engine 115 may identify anemail from a cellular phone company that was sent to the user as areminder to pay a bill and the task recognition engine 115 may determinethat the user has a bill to pay in the future based on the email. Also,for example, the task recognition engine 115 may recognize anappointment from a calendar application and associate the appointmentwith a likely task, and then associate the task with a given tasksuggestion to provide to the user. In some implementations, the querysuggestion engine 120 may identify one or more query suggestions basedon information that is provided by the task recognition engine 115. Forexample, query suggestion engine 120 may not initially identify “pay mycell phone” as a query suggestion for the query “cell phone paymentmethods,” and task recognition 115 may provide information to querysuggestion engine 120 to identify “pay my cell phone” as a querysuggestion based on additional and/or alternate similarity methods(e.g., word and/or term matching, entity mapping, pre-defined list ofcommon task suggestions).

At step 210, the query suggestions are provided to the user, includingat least one task suggestion identified at step 205. The suggestions maybe provided to the user via the computing device 105. In someimplementations, the task suggestions and/or query suggestions may beprovided to the user through a graphical user interface that shares oneor more aspects with the graphical user interfaces illustrated in FIGS.4A through 4D. In some implementations where both task suggestions andnon-task suggestions are provided to the user, the task suggestions maybe provided in a different form and/or annotated in a different mannerthan non-task suggestions to alert the user to the nature of one or moresuggestions. For example, task suggestions may be annotated with “CreateTask,” such as the task suggestion “pay my cell phone bill” in FIG. 4B.

In some implementations, a task is associated with a query suggestiononly when the confidence level that the task is related to the querysuggestion exceeds a threshold confidence level. The task recognitionengine may utilize terms in the query suggestion, attributes that areassociated with the user, and/or documents that are associated with theuser to determine the likelihood that the user has interest in beingassociated with the task. For example, query suggestion engine 120 mayidentify a query suggestion of “cell phone payment Business1” and taskrecognition engine 115 may identify a task of “pay my cell phone bill toBusiness1” as related to the query suggestion. Task recognition engine115 may further identify that the user has a cellular phone contractwith “Business2” based on information identified in an email of theuser, and determine that the user is less likely to have interest inpaying a cellular phone bill to “Business1.” Additionally, taskrecognition engine 115 may lower the ranking of the query suggestion“pay my cell phone bill to Business1” in the provided query suggestions.

At step 215, a selection of a task suggestion from the query suggestionsthat were provided to the user at step 210 is received. In someimplementations, the user may select a task suggestion utilizing acomputing device that shares one or more aspects with the computingdevice 105. In some implementations, the user may select a tasksuggestion by indicating the selection from a graphical list ofsuggestions that may share one or more aspects with the graphical userinterfaces of FIGS. 4A and 4B. In some implementations, the user mayadditionally provide information associated with a task when submittinga selected task suggestion to the system. For example, the user mayadditionally provide a web address for an online bill pay system alongwith a selection of a task suggestion that is related to paying acellular phone bill. In some implementations, one or more selected tasksuggestions may additionally trigger one or more additional actions whenthe query suggestion is selected by the user, such as adding anappointment to a calendar, sending an email, directing the user to awebsite, and/or prompting the user to enter additional informationutilizing a prompt screen that may share one or more characteristicswith the graphical user interface in FIG. 4E. In some implementations,the selected task suggestion may be associated with the task ofutilizing the task suggestion as a search query suggestion to submit toa search engine that may share one or more aspects with search engine125. In some implementations, the selected task may additionally oralternatively be submitted by the user with a selected task type todifferentiate between multiple tasks that may be associated with a tasksuggestion. For example, the task suggestion “go to cellular phonestore” may be associated with a task of purchasing a new cellular phoneand may additionally be associated with a task of paying a cellularphone bill. “Go to cellular phone store” may be provided to the usertwice and annotated differently to inform the user of the task that isassociated with each task suggestion that would otherwise appear to theuser to be identical (e.g., “Go to cellular phone store to purchase newphone” and “Go to cellular phone store to pay cellular phone bill”).Also, for example, one task suggestion may be provided to the user andthe user may be prompted to further provide a task type with the tasksuggestion, such as utilizing a graphical user interface that thatshares one or more aspects with the interface illustrated in FIG. 4E anddescribed herein. In some implementations, multiple tasks may beassociated with the user when the user selects a task suggestion that isassociated with multiple tasks of different task types. For example,both a reminder task and an event task may be associated with the userwhen the user selects the task suggestion “birthday of Bob.”

In some implementations, the received query suggestion may be utilizedboth as a search query and to associate a task with a user. For example,the query suggestion “pay my cell phone” may be submitted to the searchengine 125 in addition to the query suggestion being utilized toassociate a task with a user as described in step 220. The user may beprovided with search results based on the selected query suggestion inaddition to a task being associated with the user. In someimplementations, query suggestions may be utilized only to associatetasks with a user and no search results may be provided to the user.

At step 220, a task is associated with the user based on the tasksuggestion that was received at step 215. In some implementations, thetask associated with the user may include a task type and/or additionalinformation that has been provided by the user when the user selects atask suggestion. In some implementations, additional information may beassociated with a task with a method that shares one or more steps withthe method illustrated in FIG. 3 and described herein. In someimplementations, the task association, task type, and/or additionalinformation are stored in one or more databases that may share one ormore aspects with content database 130.

Referring to FIG. 3, a flow chart illustrating an example method ofdetermining additional information related to completing a taskassociated with a user is provided. Other implementations may performthe steps in a different order, omit certain steps, and/or performdifferent and/or additional steps than those illustrated in FIG. 3. Thesteps of the method illustrated in FIG. 3 may be performed by one ormore components illustrated in FIG. 1.

At step 300, a task that is associated with a user is identified. Thetask may be associated with the user via the method that is illustratedin FIG. 2 and described herein. For example, a task may be associatedwith the user based on the user selecting a task suggestion from aplurality of suggestions that were provided to the user based on apartial query or completed query that was provided by the user. In someimplementations, the task may be associated with the user based on otheractions of the user. For example, the task may be associated with theuser based on the user adding an appointment to a calendar applicationexecuting on computing device 105. Also, for example, a task may beassociated with a user based on the content of one or more user-editeddocuments.

At step 305, additional information regarding completing the task isdetermined. Additional information may include information thatfacilitates the completion of the task. For example, a task to pay acellular phone bill may additionally be associated with a webpage and/ora telephone number to facilitate the user in paying a cellular phonebill. In some implementations, the additional information may beprovided by the user. For example, the task recognition engine 115 mayidentify the task of “pay my cell phone” and prompt the user to enteradditional information related to completing the task, such as the duedate, a website for submitting payment, and/or an amount that is to bepaid. The prompt to the user may share one or more aspects with thegraphical user interface that is illustrated in FIG. 4E and describedherein.

In some implementations, task recognition engine 115 may determineadditional information about a task utilizing an entity database thatmay share one or more aspects with content database 130. For example,the entity associated with “Business1” may be determined to beadditional information that is associated with a task based on userinput from a prompt and/or from one or more documents associated withthe user, such as emails, calendars, contacts, and/or recently visitedwebsites. Task recognition engine 115 may determine additionalinformation about “Business1,” such as the address, telephone number,and/or website of “Business 1” based on associations between the entityassociated with “Business1” and one or more additional entities in anentity database. Such additional information may be further associatedwith the task and may be utilized to provide the user with informationthat is pertinent to completing the task.

In some implementations, task recognition engine 115 may associateadditional information with a task based on one or more words and/orphrases in the provided query. For example, the user may provide a query“pay cell phone bill Business 1” and the task recognition engine 115 maydetermine that the task of paying a cellular phone bill is related tothe query. The task recognition engine 115 may further associate“Business 1” with the task as additional information that is related tocompletion of the task. In some implementations, information in theprovided query may be utilized to locate additional information in anentity database. For example, the task recognition engine 115 mayidentify the entity associated with “Business 1” from the query “pay mycell phone bill Business1” and identify additional information relatedto the entity based on the presence of “Business 1” in the query.

At step 310, the additional information regarding the completion of thetask is associated with the task. The association of the additionalinformation and the task may be stored in a database that may share oneor more aspects with content database 130. In some implementations, theadditional information associated with a task may be utilized by searchengine 125 for future queries and/or may be utilized by task recognitionengine 115 to identify additional task suggestions, tasks, and/oradditional information about additional tasks. For example, a task maybe associated with a user for paying a cellular phone bill that isassociated with “Business 1” as the name of the cellular phone provider.In response to selection of a future query of “cancel my cell phone,” itmay be determined that the user is likely to have “Business 1” as acellular phone provider based on the additional information associatedwith the task in the content database 130 and “Business 1” may beassociated with the new task of cancelling cellular service.

Although methods of providing task suggestions and associating taskswith users are illustrated in the Figures, other methods mayadditionally and/or alternatively be utilized to identify tasksuggestions and associate tasks with a user based on a query. Certainimplementations of the methods of providing task suggestions have beendescribed as taking place in a substantially real time environment.However, one or more aspects of methods described herein may beimplemented in an offline mode. For example, implementations of methodsdescribed herein may be utilized to identify a task suggestion and/orassociate a task suggestion with a user in response to a query that maybe made available for utilization in a real time environment inprocessing query suggestions.

FIGS. 4A through 4G illustrate graphical user interfaces that can beused to allow a user to enter a query, provide query suggestions to theuser, and to allow the user to select a query suggestion based on thequery. In some implementations, selecting one or more query suggestionsfrom the provided query suggestions may result in a web search based onthe terms of the query suggestion. In some implementations, thegraphical user interface may be part of an application, such as acalendar application and/or an email application. In someimplementations, one or more of the provided query suggestions may be atask suggestion and a task may be associated with a user based on thetask suggestion that is selected by the user. In some implementations,selecting a task suggestion from a provided list of query suggestionsmay additionally initiate a web search in addition to associating a taskwith a user. In some implementations, selecting a task suggestion willresult in a task suggestion being associated with the user without asearch being conducted.

Referring to FIG. 4A, a partial screenshot of an example environmentthat can be used to provide query suggestion results to a user isillustrated. In FIG. 4A, the partial screenshot includes a search fieldrepresentation 400A and a search button representation 410A. In thisexample, the user has entered the partial search query “pa” into thesearch field representation 400A and a drop down menu 420A of the searchfield is displayed. A module that may share one or more characteristicswith query suggestion engine 120 may identify one or more candidatequery suggestions that may be associated with the prefix “pa.” A modulethat may share one or more characteristics with task recognition engine115 may identify one or more candidate task suggestions that may beassociated with the prefix “pa” in addition to the query suggestionsprovided by query suggestion engine 120. The query suggestion engine 120may identify query suggestions based on, for example, a list of pastuser queries, a list of automatically generated queries, and/or realtime automatically generated queries. The task recognition engine 115may identify task suggestions based on, for example, similaritiesbetween a query suggestion and an aspect of a task, and/or similaritybetween a potential task suggestion and one or more likely tasks of theuser based on additional information that is known about a user and/orthat is provided by a user. Query suggestion engine 120 may associate ascore with each identified query suggestion and/or task suggestion, andrank the suggestions based on the associated scores. The drop down menu420A includes four query suggestions that are based on the partialsearch query “pa,” including the task suggestion “pay my cell phonebill.”

The user may optionally choose any of the suggestions and utilize thesuggestion as a completed query or the basis for a completed query toretrieve information based on the identified query suggestion. In someimplementations, the user may select a query suggestion that isadditionally associated with a task (i.e., a task suggestion), and theassociated task may be associated with the user. In someimplementations, the user may request additional display sets of querysuggestions to be displayed. For example, in some implementations a usermay scroll within the drop down menu 420A to display one or moreadditional query suggestions from further display sets. In someimplementations, the user may indicate that the search query that isentered into search field 400A is complete by selecting search button410A. In some implementations, one or more of the query suggestions indrop down menu 420A may be selectable and the user may choose a querysuggestion by selecting a suggestion in drop down menu 420A. In someimplementations, query suggestions that are task suggestions may bedisplayed differently than other query suggestions and a task may beassociated with the user when the user selects a task suggestion. Forexample, task suggestions may be displayed in an alternate color, and aseparate column, and/or marked with an indication to distinguish querysuggestions from task suggestions as illustrated in FIG. 4B anddescribed herein.

Referring to FIG. 4B, another partial screenshot of an exampleenvironment that can be used to provide query suggestion results to auser including a task suggestion is illustrated. In FIG. 4B, the partialscreen shot includes a search field representation 400B and a searchbutton representation 410B. The query suggestions in drop down menu 420Bare the same query suggestions as the query suggestions in FIG.4A withan entry in the list highlighted by the hovering over of a cursor 440B.The “pay my cell phone bill” suggestion is illustrated as a tasksuggestion and includes the words “Create Task” to notify the user thatthe entry is associated with a task in addition to or instead of a querysuggestion. In some implementations, task suggestions may additionallybe marked with, for example, a different color, a graphical icon, or ina different column to differentiate task suggestions from querysuggestions. In some implementations, “Create Task” may be selectable,and selecting “Create Task” may indicate that the user would like toassociate the task associated with “pay my cell phone bill” with theuser. In some implementations, the user may be prompted for additionalinformation about the task if the user selects the “Create Task” link.

Referring to FIG. 4C, another partial screenshot of an example graphicaluser interface that can be used to provide task suggestions to a user isillustrated. The graphical user interface includes a task fieldrepresentation 400C and submit task button 410C to allow the user toselect a task suggestion that is associated with a selected task and/orto submit one or more entries to a search engine as a search query. Insome implementations, the example graphical user interface of FIG. 4Cmay be part of a task entry interface of one or more applications andthe selected entry in task field representation 400C may not besubmitted to a search engine (i.e., all selected entries may associatetasks with the user and no selected tasks produce search results). Thetask field representation 400C includes the partial query “pay my” thathas been entered by the user. The task suggestions in drop down menu420C are task suggestions that are based on information that has beenidentified based on user attributes and/or one or more user documentsand that share similarities with the query in task field 400C. Theprovided task suggestions are associated with tasks that are potentiallyof interest to the user based on, for example, information that wasidentified from calendar entries of the user, emails of the user,previously visited webpages of the user, and/or contacts from anelectronic address book of the user. For example, the task recognitionengine 115 may identify the phrase “pay my” to be potentially related toa task that is related to the user paying a bill. Task recognitionengine 115 may identify one or more entries in a calendar applicationthat are related to bills and provide the user with the task suggestionsin drop down menu 420C that are associated with tasks of paying bills.The user may select a task suggestion from the drop down menu 420C andselect the submit task button 410C and the task corresponding to theselected task suggestion may be associated with the user. In someimplementations, query suggestions that are not associated with a taskmay be provided in drop down menu 420C in addition to task suggestions.In some implementations, task suggestions may be annotated with the tasktype of the user and/or task suggestions may be otherwise displayeddifferently than non-task query suggestions as illustrated in FIG. 4Band described herein.

Referring to FIG. 4D, another partial screenshot of an example graphicaluser interface that can be used to provide query suggestions to a userbased on entity relationships is illustrated. The graphical userinterface includes a task field representation 400D and submit taskbutton 410D to allow the user to select a task suggestion that isassociated with a selected task. The task suggestions in drop down menu420D are query suggestions that are based on similarities between apartial query suggestion that has been provided by the user in taskfield 400D and one or more entities from an entity database. The partialquery “cell p” has been utilized to identify the entity associated with“cell phone” based on similarities between the partial query and thetext “cell phone” (e.g., prefix-based matching).

In some implementations, one or more of the identified query suggestionsmay be boosted or lowered in ranking of importance based information,attributes, and/or documents that are associated with the user. In someimplementations, the task recognition engine 115 may provide querysuggestion engine 120 with additional information about one or morequery suggestions to affect the ranking of a query suggestion, such asuser attributes and/or documents associated with the user. For example,the query suggestion engine 120 may identify an entity associated with“cell phone,” which may be mapped with entities associated with theconcepts of “paying,” “renewing,” and “purchasing” based on thoseactions being possible actions that may be associated with a cell phone.Query suggestion engine 120 may identify query suggestions of “Pay acell phone bill,” “Renew a cellular phone contract,” and “Make a phonecall” based on the related entities in the database, and the tasksuggestions may be filtered, ranked, and/or otherwise provided to theuser based on user attributes and/or information identified from one ormore user documents. For example, the task suggestion “pay a cell phonebill” may be boosted in ranking based on, for example, informationidentified in emails about a cellular phone bill, calendars entries,and/or webpage navigation history of the user that indicates that theuser is more likely to have interest in a task to pay a cellular phonebill than the user has interest in the task of “calling on a cellphone.” Also, for example, task suggestion “Call on a cell phone” mayrelated to the entity “cell phone,” and query suggestion engine 120 maylower the rank of the task suggestion related to calling on a cellularphone based on information that the user does not own a cellular phone.

Referring to FIG. 4E, another partial screenshot of an example graphicaluser interface that can be used to prompt a user to provide additionalinformation about a task is illustrated. The illustrated graphicalinterface may be provided to the user at step 305 of the method in FIG.3 to determine additional information about a task that has beenassociated with a user. Data entered into the fields of the graphicaluser interface may be utilized in step 310 to associate the additionalinformation with the task. In some implementations, the user may beprompted to enter the information when the user performs an additionalstep, such as selecting a task from a graphical user interface thatshares one or more characteristics with the interfaces illustrated inFIGS. 4A through 4D, when the user opens a particular application (e.g.,a calendar application, a contacts application, etc.), and/or when theuser unlocks or activates a mobile electronic device. In someimplementations, the graphical user interface may display additionaland/or alternative fields based on the type of the task, the device thatis utilized to display the interface to the user, and/or the applicationthat is utilized to display the interface to the user. In someimplementations, the graphical user interface may include buttons orother interface elements to permit the user to associate the providedinformation with multiple and/or alternative tasks. For example, thegraphical user interface may include a button to associate additionalprovided information with an event task and/or with a reminder task.

In some implementations, a task may be further associated with a tasktype as described herein. The indication for a task suggestion in thepartial graphical interface of FIG. 4B may include an indication of thetask type that is associated with a task suggestion. For example, thetask suggestion “pay my cell phone bill” may be associated with areminder task type. The indication that is displayed with the tasksuggestion may be representative of the task type, such as “CreateReminder.” Also, for example, a task suggestion that is associated witha purchase task type may be displayed with the indication “CreatePurchase Task.” In some implementations, one task suggestion may beassociated with multiple tasks with different task types. In some ofthose implementations, one task suggestion may be displayed withmultiple task type indications. In some implementations, the same tasksuggestion may appear in the graphical interface multiple times withdifferent task type indications. For example, “pay my cell phone bill”may be associated with a purchase task (e.g., to enable auto payment, tolocate a retail store) and a reminder task (e.g., to remind the user topay the bill). In some implementations, “pay my cell phone bill” may beannotated in the list with both “Create Reminder” and “Create PurchaseTask.” Also, for example, “pay my cell phone bill” may be displayed inthe list annotated with “Create Reminder” and displayed a second timewith the annotation “Create Purchase Task.”

Referring to FIG. 4F, a partial screenshot of an example graphical userinterface that can be used to provide query suggestions and additionaltask completion information to a user is provided. The graphical userinterface includes a task field representation 400F and search button410F. In this example, the user has entered the partial search query“Contact Company 1” into the task field representation and tasksuggestions 415F, 420F, and 425F are displayed. A module that shares oneor more characteristics with query suggestion engine 120 and/or taskrecognition engine 115 may identify one or more query suggestions and/orcandidate task suggestions based on the query that was entered by theuser and provide the suggestions to the user. In some implementations,selecting a suggestion may submit the selection to a search engine.Additionally or alternatively, selecting a candidate task suggestion mayassociate a task with the user. For example, selecting call tasksuggestion 415F may associate a task to call Company 1 with the user.Also, for example, selecting call task suggestion 415F may populate adialing application of the user with the phone number of Company and/orset a calendar reminder to call Company 1 in a calendar application ofthe user. In some implementations, the partial query that was entered bythe user in search field representations 400F may be submitted to asearch engine as a partial search query when the user selects searchbutton 410F. The task field representation 400F includes partial query“Contact Company 1” that has been entered by the user. The tasksuggestions 415F, 420F, and 425F are task suggestions that may be basedon information that has been identified from user attributes, userdocuments, and/or one or more databases as described herein. Forexample, task recognition engine 115 may identify one or more entries ina contacts application of the user that are related to Company 1 andprovide the user with the task suggestions that are associated withtasks of contacting Company 1 based on an identified phone number, emailaddress, and/or mailing address. Also, for example, task recognitionengine 115 may identify one or more entities in an entity database thatare associated with Company 1 and identify, for example, a phone numberfor Company 1 from information that is associated with the identifiedentity. Additional information that is identified for a suggested taskmay be provided with the task suggestion. For example, for the call tasksuggestion 415F, the user is provided with a phone number in addition toa description of the task which may be identified from, for example, acontacts application of the user. Also, for example, email tasksuggestion 420F includes an email address for the entity “Company 1”which may be identified from, for example, browser history of the userthat includes viewing a contact webpage for “Company 1.” Also, forexample, mail task suggestion 425F is provided with a street address forthe entity “Company 1,” which may be identified from, for example, anelectronic bill from Company 1 that was received by the user.

The task suggestions 415F, 420F, and 425F are annotated with icons thatidentify the task type for each of the provided task suggestions. Forexample, the call task suggestion 415F includes a telephone icon toprovide the user with a graphical indication of the type of the task. Insome implementations, the icon may be selectable and the user may selectthe icon to indicate that the task that is associated with the iconshould be associated with the user; and the user may select the querysuggestion (e.g., selecting the text of the task suggestion withoutselecting the icon) to utilize the entry as search query suggestionwithout associating a task with the user. In some implementations,selecting any portion of a provided task suggestion may associate thetask of the selected task suggestion with the user.

Referring to FIG. 4G, a partial screenshot of an example graphical userinterface that can be used to provide query suggestions with task typeindications to a user is provided. The graphical user interface includesa task field representation 400G and search button 410G. In someimplementations, selecting the search button 410G may submit the partialquery that is entered in task field representation 400G as a searchquery. The task field representation 400G includes partial query“contact b” that has been entered by the user. The dropdown menu 420Gincludes task suggestions that are based on information that has beenidentified from user attributes, one or more user documents, and/or oneor more databases as described herein. The provided task suggestions areassociated with tasks that are potentially of interest to the user basedon, for example, information that is identified from calendar entries ofthe user, emails of the user, previously visited webpages of the user,and/or contacts from an electronic address book of the user. Icons nextto each task suggestion indicate different types of tasks that may beassociated with the user based on identified potential task completionsteps. For example, “Contact Bill” is followed by icons for emailing,phoning, and mailing tasks. Task recognition engine 115 may identify oneor more entries in a contacts application, email, and/or document in thebrowsing history of the user, and identify an email address, a phonenumber, and a mailing address associated with “Bill.” Also, for example,the entry for “Betty” includes an email task icon and a phone task icon,but not a mailing icon. This may indicate to the user that email andphone contact information has been identified for “Betty,” and tasksrelating to emailing and/or phoning “Betty” may be associated with theuser. In some implementations, the icons may be selectable, andselecting an icon will associate the task with the task type that isrepresented by the icon that was selected. For example, clicking on thephone icon next to “Contact Bill” may associate a task of “Call Bill”with the user. Also, for example, selecting the email icon next to“Contact Bill” may associate an “Email Bill” task with the user.

FIG. 5 is a block diagram of an example computer system 510. Computersystem 510 typically includes at least one processor 514 whichcommunicates with a number of peripheral devices via bus subsystem 512.These peripheral devices may include a storage subsystem 524, including,for example, a memory subsystem 526 and a file storage subsystem 528,user interface input devices 522, user interface output devices 520, anda network interface subsystem 516. The input and output devices allowuser interaction with computer system 510. Network interface subsystem516 provides an interface to outside networks and is coupled tocorresponding interface devices in other computer systems.

User interface input devices 522 may include a keyboard, pointingdevices such as a mouse, trackball, touchpad, or graphics tablet, ascanner, a touchscreen incorporated into the display, audio inputdevices such as voice recognition systems, microphones, and/or othertypes of input devices. In general, use of the term “input device” isintended to include all possible types of devices and ways to inputinformation into computer system 510 or onto a communication network.

User interface output devices 520 may include a display subsystem, aprinter, a fax machine, or non-visual displays such as audio outputdevices. The display subsystem may include a cathode ray tube (CRT), aflat-panel device such as a liquid crystal display (LCD), a projectiondevice, or some other mechanism for creating a visible image. Thedisplay subsystem may also provide non-visual display such as via audiooutput devices. In general, use of the term “output device” is intendedto include all possible types of devices and ways to output informationfrom computer system 510 to the user or to another machine or computersystem.

Storage subsystem 524 stores programming and data constructs thatprovide the functionality of some or all of the modules describedherein. For example, the storage subsystem 524 may include the logic toidentify a task suggestion based on a user query and associate a taskwith the user based on a selected task suggestion that is associatedwith the task.

These software modules are generally executed by processor 514 alone orin combination with other processors. Memory 526 used in the storagesubsystem can include a number of memories including a main randomaccess memory (RAM) 530 for storage of instructions and data duringprogram execution and a read only memory (ROM) 532 in which fixedinstructions are stored. A file storage subsystem 528 can providepersistent storage for program and data files, and may include a harddisk drive, a floppy disk drive along with associated removable media, aCD-ROM drive, an optical drive, or removable media cartridges. Themodules implementing the functionality of certain implementations may bestored by file storage subsystem 528 in the storage subsystem 524, or inother machines accessible by the processor(s) 514.

Bus subsystem 512 provides a mechanism for letting the variouscomponents and subsystems of computer system 510 communicate with eachother as intended. Although bus subsystem 512 is shown schematically asa single bus, alternative implementations of the bus subsystem may usemultiple busses.

Computer system 510 can be of varying types including a workstation,server, computing cluster, blade server, server farm, or any other dataprocessing system or computing device. Due to the ever-changing natureof computers and networks, the description of computer system 510depicted in FIG. 5 is intended only as a specific example for purposesof illustrating some implementations. Many other configurations ofcomputer system 510 are possible having more or fewer components thanthe computer system depicted in FIG. 5.

While several inventive implementations have been described andillustrated herein, a variety of other means and/or structures forperforming the function and/or obtaining the results and/or one or moreof the advantages described herein may be utilized, and each of suchvariations and/or modifications is deemed to be within the scope of theinventive implementations described herein. More generally, allparameters, dimensions, materials, and configurations described hereinare meant to be exemplary and that the actual parameters, dimensions,materials, and/or configurations will depend upon the specificapplication or applications for which the inventive teachings is/areused. Those skilled in the art will recognize, or be able to ascertainusing no more than routine experimentation, many equivalents to thespecific inventive implementations described herein. It is, therefore,to be understood that the foregoing implementations are presented by wayof example only and that, within the scope of the appended claims andequivalents thereto, inventive implementations may be practicedotherwise than as specifically described and claimed. Inventiveimplementations of the present disclosure are directed to eachindividual feature, system, article, material, kit, and/or methoddescribed herein. In addition, any combination of two or more suchfeatures, systems, articles, materials, kits, and/or methods, if suchfeatures, systems, articles, materials, kits, and/or methods are notmutually inconsistent, is included within the inventive scope of thepresent disclosure.

All definitions, as defined and used herein, should be understood tocontrol over vocabulary definitions, definitions in documentsincorporated by reference, and/or ordinary meanings of the definedterms.

The indefinite articles “a” and “an,” as used herein in thespecification and in the claims, unless clearly indicated to thecontrary, should be understood to mean “at least one.”

The phrase “and/or,” as used herein in the specification and in theclaims, should be understood to mean “either or both” of the elements soconjoined, i.e., elements that are conjunctively present in some casesand disjunctively present in other cases. Multiple elements listed with“and/or” should be construed in the same fashion, i.e., “one or more” ofthe elements so conjoined. Other elements may optionally be presentother than the elements specifically identified by the “and/or” clause,whether related or unrelated to those elements specifically identified.Thus, as a non-limiting example, a reference to “A and/or B”, when usedin conjunction with open-ended language such as “comprising” can refer,in one implementation, to A only (optionally including elements otherthan B); in another implementation, to B only (optionally includingelements other than A); in yet another implementation, to both A and B(optionally including other elements); etc.

As used herein in the specification and in the claims, “or” should beunderstood to have the same meaning as “and/or” as defined above. Forexample, when separating items in a list, “or” or “and/or” shall beinterpreted as being inclusive, i.e., the inclusion of at least one, butalso including more than one, of a number or list of elements, and,optionally, additional unlisted items. Only terms clearly indicated tothe contrary, such as “only one of” or “exactly one of,” or, when usedin the claims, “consisting of,” will refer to the inclusion of exactlyone element of a number or list of elements. In general, the term “or”as used herein shall only be interpreted as indicating exclusivealternatives (i.e. “one or the other but not both”) when preceded byterms of exclusivity, such as “either,” “one of,” “only one of,” or“exactly one of.” “Consisting essentially of,” when used in the claims,shall have its ordinary meaning as used in the field of patent law.

As used herein in the specification and in the claims, the phrase “atleast one,” in reference to a list of one or more elements, should beunderstood to mean at least one element selected from any one or more ofthe elements in the list of elements, but not necessarily including atleast one of each and every element specifically listed within the listof elements and not excluding any combinations of elements in the listof elements. This definition also allows that elements may optionally bepresent other than the elements specifically identified within the listof elements to which the phrase “at least one” refers, whether relatedor unrelated to those elements specifically identified. Thus, as anon-limiting example, “at least one of A and B” (or, equivalently, “atleast one of A or B,” or, equivalently “at least one of A and/or B”) canrefer, in one implementation, to at least one, optionally including morethan one, A, with no B present (and optionally including elements otherthan B); in another implementation, to at least one, optionallyincluding more than one, B, with no A present (and optionally includingelements other than A); in yet another implementation, to at least one,optionally including more than one, A, and at least one, optionallyincluding more than one, B (and optionally including other elements);etc.

It should also be understood that, unless clearly indicated to thecontrary, in any methods claimed herein that include more than one stepor act, the order of the steps or acts of the method is not necessarilylimited to the order in which the steps or acts of the method arerecited.

What is claimed is:
 1. A method implemented by one or more processors,comprising: identifying a query, the query being entered by a user in agraphical interface displayed by a computing device of the user;identifying a plurality of suggestions based on similarity between thesuggestions and the query, the suggestions including: at least onenon-task suggestion, and at least one task suggestion associated with atleast one task; prior to user input that indicates completion of thequery, providing the task suggestion and the non-task suggestion forpresentation to the user in the graphical interface; monitoring for auser selection of the task suggestion or the non-task suggestion;wherein in response to the user selection being of the task suggestion:providing a task information prompt for creating the at least one taskassociated with the at least one task suggestion, receiving, based onuser input received at the computing device responsive to providing thetask information prompt, additional information from the user that isrelated to the at least one task, the additional information includingone or both of date information and time information associated with theat least one task, and storing, in one or more databases in associationwith the user, the received additional information that is received inresponse to the task information prompt, wherein no search results areprovided in response to the user selection of the task suggestion; andwherein in response to the user selection being of the non-tasksuggestion: submitting the non-task suggestion as a search query toobtain search results responsive to the non-task suggestion.
 2. Themethod of claim 1, further comprising determining the at least one taskassociated with the task suggestion.
 3. The method of claim 2, whereindetermining the at least one task comprises determining the at least onetask based on one or more terms of the task suggestion.
 4. The method ofclaim 2, wherein determining the at least one task comprises determiningthe at least one task based on user data associated with the user. 5.The method of claim 1, wherein providing the task information promptcomprises providing a prompt graphical user interface.
 6. The method ofclaim 5, wherein the prompt graphical user interface includes aplurality of fields and wherein the received additional information isreceived in response to user interface input directed at one or more ofthe fields.
 7. The method of claim 5, further comprising selecting theprompt graphical interface based on a task type of the at least onetask.
 8. The method of claim 1, wherein the received additionalinformation includes the date information, and wherein the dateinformation includes a due date for the at least one task.
 9. The methodof claim 1, wherein the received additional information includeslocation information, and wherein the location information includes alocation for the at least one task.
 10. The method of claim 1, furthercomprising, in response to the user selection being of the tasksuggestion: identifying information associated with the at least onetask based on one or more terms of the query entered by the user in thegraphical interface displayed by the computing device of the user, andwherein storing the received additional information comprises storing,in one or more of the databases in association with the user, theinformation associated with the at least one task.
 11. The method ofclaim 10, wherein the task information prompt includes one or morefields that are automatically populated with the information associatedwith the at least one task.
 12. A system comprising: memory storinginstructions; one or more processors operable to execute theinstructions to: identify a query entered by a user in a graphicalinterface displayed by a computing device of the user; identify aplurality of suggestions based on similarity between the suggestions andthe query, the suggestions including: at least one non-task suggestion,and at least one task suggestion associated with at least one task;prior to user input that indicates completion of the query, provide thetask suggestion and the non-task suggestion for presentation to the userin the graphical interface; monitor for a user selection of the tasksuggestion or the non-task suggestion; wherein in response to the userselection being of the task suggestion: provide a task informationprompt for creating the at least one task associated with the at leastone task suggestion, receiving, based on user input received at thecomputing device responsive to providing the task information prompt,additional information from the user that is related to the at least onetask, the additional information including one or both of dateinformation and time information associated with the at least one task,and store, in one or more databases in association with the user, thereceived additional information that is received in response to the taskinformation prompt, wherein no search results are provided in responseto the user selection of the task suggestion; and wherein in response tothe user selection being of the non-task suggestion: submit the non-tasksuggestion as a search query to obtain search results responsive to thenon-task suggestion.
 13. The system of claim 12, wherein one or more ofthe processors, in executing the instructions, are further to determinethe at least one task associated with the task suggestion.
 14. Thesystem of claim 13, wherein in determining the at least one task, one ormore of the processors are to determine the at least one task based onone or more terms of the task suggestion.
 15. The system of claim 13,wherein in determining the at least one task, one or more of theprocessors are to determine the at least one task based on user dataassociated with the user.
 16. The system of claim 12, wherein the taskinformation prompt is a prompt graphical user interface.
 17. The systemof claim 16, wherein the prompt graphical user interface includes aplurality of fields and wherein the received additional information isreceived in response to user interface input directed at one or more ofthe fields.
 18. The system of claim 16, wherein one or more of theprocessors, in executing the instructions, are further to select theprompt graphical interface based on a task type of the at least onetask.
 19. The system of claim 12, wherein the received additionalinformation includes the date information, and wherein the dateinformation includes a due date for the at least one task.
 20. At leastone non-transitory computer-readable medium storing instructionsexecutable by one or more processors to cause the one or more processorsto perform the following operations: identifying a query, the querybeing entered by a user in a graphical interface displayed by acomputing device of the user; identifying a plurality of suggestionsbased on similarity between the suggestions and the query, thesuggestions including: at least one non-task suggestion, and at leastone task suggestion associated with at least one task; prior to userinput that indicates completion of the query, providing the tasksuggestion and the non-task suggestion for presentation to the user inthe graphical interface; monitoring for a user selection of the tasksuggestion or the non-task suggestion; wherein in response to the userselection being of the task suggestion: providing a task informationprompt for creating the at least one task associated with the at leastone task suggestion, receiving, based on user input received at thecomputing device responsive to providing the task information prompt,additional information from the user that is related to the at least onetask, the additional information including one or both of dateinformation and time information associated with the at least one task,and storing, in one or more databases in association with the user, thereceived additional information that is received in response to the taskinformation prompt, wherein no search results are provided in responseto the user selection of the task suggestion; and wherein in response tothe user selection being of the non-task suggestion: submitting thenon-task suggestion as a search query to obtain search resultsresponsive to the non-task suggestion.